C++ Quaterniond::setIdentity方法代码示例

int main(int argc, char **argv)
{
  int num_points = 0;

  // check for arg, # of points to use in projection SBA
  if (argc > 1)
    num_points = atoi(argv[1]);

  double euc_noise = 0.1;      // noise in position, m
  double pix_noise = 1.0;       // pixel noise
  //  double outlier_ratio = 0.1;


  SparseOptimizer optimizer;
  optimizer.setVerbose(false);

  // variable-size block solver
  BlockSolverX::LinearSolverType * linearSolver
      = new LinearSolverCSparse<g2o
        ::BlockSolverX::PoseMatrixType>();


  BlockSolverX * solver_ptr
      = new BlockSolverX(linearSolver);

  g2o::OptimizationAlgorithmLevenberg* solver = new g2o::OptimizationAlgorithmLevenberg(solver_ptr);

  optimizer.setAlgorithm(solver);

  vector<Vector3d> true_points;
  for (size_t i=0;i<1000; ++i)
  {
    true_points.push_back(Vector3d((Sample::uniform()-0.5)*3,
                                   Sample::uniform()-0.5,
                                   Sample::uniform()+10));
  }


  // set up camera params
  Vector2d focal_length(500,500); // pixels
  Vector2d principal_point(320,240); // 640x480 image
  double baseline = 0.075;      // 7.5 cm baseline

  // set up camera params and projection matrices on vertices
  g2o::VertexSCam::setKcam(focal_length[0],focal_length[1],
                           principal_point[0],principal_point[1],
                           baseline);


  // set up two poses
  int vertex_id = 0;
  for (size_t i=0; i<2; ++i)
  {
    // set up rotation and translation for this node
    Vector3d t(0,0,i);
    Quaterniond q;
    q.setIdentity();

    Eigen::Isometry3d cam;           // camera pose
    cam = q;
    cam.translation() = t;

    // set up node
    VertexSCam *vc = new VertexSCam();
    vc->setEstimate(cam);
    vc->setId(vertex_id);      // vertex id

    cerr << t.transpose() << " | " << q.coeffs().transpose() << endl;

    // set first cam pose fixed
    if (i==0)
      vc->setFixed(true);

    // make sure projection matrices are set
    vc->setAll();

    // add to optimizer
    optimizer.addVertex(vc);

    vertex_id++;                
  }

  // set up point matches for GICP
  for (size_t i=0; i<true_points.size(); ++i)
  {
    // get two poses
    VertexSE3* vp0 = 
      dynamic_cast<VertexSE3*>(optimizer.vertices().find(0)->second);
    VertexSE3* vp1 = 
      dynamic_cast<VertexSE3*>(optimizer.vertices().find(1)->second);

    // calculate the relative 3D position of the point
    Vector3d pt0,pt1;
    pt0 = vp0->estimate().inverse() * true_points[i];
    pt1 = vp1->estimate().inverse() * true_points[i];

    // add in noise
    pt0 += Vector3d(Sample::gaussian(euc_noise ),
                    Sample::gaussian(euc_noise ),
                    Sample::gaussian(euc_noise ));
//.........这里部分代码省略.........

int main()
{
  double euc_noise = 0.01;       // noise in position, m
  //  double outlier_ratio = 0.1;


  SparseOptimizer optimizer;
  optimizer.setVerbose(false);

  // variable-size block solver
  BlockSolverX::LinearSolverType * linearSolver = new LinearSolverDense<g2o::BlockSolverX::PoseMatrixType>();
  BlockSolverX * solver_ptr = new BlockSolverX(linearSolver);
  g2o::OptimizationAlgorithmLevenberg* solver = new g2o::OptimizationAlgorithmLevenberg(solver_ptr);

  optimizer.setAlgorithm(solver);

  vector<Vector3d> true_points;
  for (size_t i=0;i<1000; ++i)
  {
    true_points.push_back(Vector3d((Sample::uniform()-0.5)*3,
                                   Sample::uniform()-0.5,
                                   Sample::uniform()+10));
  }


  // set up two poses
  int vertex_id = 0;
  for (size_t i=0; i<2; ++i)
  {
    // set up rotation and translation for this node
    Vector3d t(0,0,i);
    Quaterniond q;
    q.setIdentity();

    Eigen::Isometry3d cam; // camera pose
    cam = q;
    cam.translation() = t;

    // set up node
    VertexSE3 *vc = new VertexSE3();
    vc->setEstimate(cam);

    vc->setId(vertex_id);      // vertex id

    cerr << t.transpose() << " | " << q.coeffs().transpose() << endl;

    // set first cam pose fixed
    if (i==0)
      vc->setFixed(true);

    // add to optimizer
    optimizer.addVertex(vc);

    vertex_id++;                
  }

  // set up point matches
  for (size_t i=0; i<true_points.size(); ++i)
  {
    // get two poses
    VertexSE3* vp0 = 
      dynamic_cast<VertexSE3*>(optimizer.vertices().find(0)->second);
    VertexSE3* vp1 = 
      dynamic_cast<VertexSE3*>(optimizer.vertices().find(1)->second);

    // calculate the relative 3D position of the point
    Vector3d pt0,pt1;
    pt0 = vp0->estimate().inverse() * true_points[i];
    pt1 = vp1->estimate().inverse() * true_points[i];

    // add in noise
    pt0 += Vector3d(Sample::gaussian(euc_noise ),
                    Sample::gaussian(euc_noise ),
                    Sample::gaussian(euc_noise ));

    pt1 += Vector3d(Sample::gaussian(euc_noise ),
                    Sample::gaussian(euc_noise ),
                    Sample::gaussian(euc_noise ));

    // form edge, with normals in varioius positions
    Vector3d nm0, nm1;
    nm0 << 0, i, 1;
    nm1 << 0, i, 1;
    nm0.normalize();
    nm1.normalize();

    Edge_V_V_GICP * e           // new edge with correct cohort for caching
        = new Edge_V_V_GICP(); 

    e->setVertex(0, vp0);      // first viewpoint

    e->setVertex(1, vp1);      // second viewpoint

    EdgeGICP meas;
    meas.pos0 = pt0;
    meas.pos1 = pt1;
    meas.normal0 = nm0;
    meas.normal1 = nm1;

    e->setMeasurement(meas);
//.........这里部分代码省略.........

void VoNode::imgCb(const sensor_msgs::ImageConstPtr& msg)
{
  // Dummy data as the real position for the system.
//  static int old = msg->header.seq;
//  if(msg->header.seq == old)
//      filtered_pose.pose.position.z = 0;
//  else{
//      filtered_pose.pose.position.z += 10.0/70.0 * (msg->header.seq-old);
//  }
//  old = msg->header.seq;

  ROS_INFO("Frame seq: %i", msg->header.seq);

#ifdef USE_ASE_IMU
  tf::StampedTransform transform;
  try{
    listener_.lookupTransform("/camera", "/worldNED",
                           ros::Time(0), transform);
  }

  catch (tf::TransformException ex){
    ROS_ERROR("%s",ex.what());
    return;
  }
#endif

  cv::Mat img;
  try {
    img = cv_bridge::toCvShare(msg, "mono8")->image;
  } catch (cv_bridge::Exception& e) {
    ROS_ERROR("cv_bridge exception: %s", e.what());
  }
  processUserActions();

//  Quaterniond quat(filtered_pose.pose.orientation.w,filtered_pose.pose.orientation.x,filtered_pose.pose.orientation.y, filtered_pose.pose.orientation.z);
//  Matrix3d orient = quat.toRotationMatrix();
//  Vector3d pos(filtered_pose.pose.position.x,filtered_pose.pose.position.y, filtered_pose.pose.position.z);

  Quaterniond quat;
  quat.setIdentity();
  Vector3d pos;
  pos.setZero();
  Matrix3d orient = quat.toRotationMatrix();

#ifdef USE_ASE_IMU
  tf::quaternionTFToEigen(transform.getRotation(), quat);
  orient = quat.toRotationMatrix();
  tf::vectorTFToEigen(transform.getOrigin(), pos);
#endif

  vo_->addImage(img, msg->header.stamp.toSec(), orient, pos);
  visualizer_.publishMinimal(img, vo_->lastFrame(), *vo_, msg->header.stamp.toSec());

  if(publish_markers_ && vo_->stage() != FrameHandlerBase::STAGE_PAUSED)
    visualizer_.visualizeMarkers(vo_->lastFrame(), vo_->coreKeyframes(), vo_->map());

  if(publish_dense_input_)
    visualizer_.exportToDense(vo_->lastFrame());

  if(vo_->stage() == FrameHandlerMono::STAGE_PAUSED)
    usleep(100000);
}